Project reports
27 October 2016 |   ByFugro Media
Fugro Author

In a world-first, a subsea part for a wellhead has been fabricated from subsea lidar data using 3D printing, opening up the possibility of creating physical 1:1 models for intervention planning.

lidar-well-cap

Cost savings can be realised from almost any situation where accurate spatial data would be beneficial to planning intervention operations
Adam Lowry, MD of 3D at Depth Pty Ltd
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Abandoned wells

Plugged and abandoned (P&A) wells located offshore Oceania in a water depth of approximately 110m, drilled decades ago and suspended at the time of drilling, required detailed measurements to achieve final abandoned status.

Access to accurate data of the manufacture and specifications of these wellheads was limited due to their age. Fugro was asked to excavate, clean, measure and identify the wellheads in order to design an appropriate ‘hot tap’ connector, to assess feasible options for abandonment.

Using its multi-role intervention vessel, the Rem Etive fitted with two ROVs, Fugro carried out subsea intervention and lidar measurement services. One of the two high specification FCV Work Class ROVs, of 3000m depth rating, contained a SL2 Subsea lidar laser, manufactured and operated by 3D at Depth. The laser was mounted on the crash bar of the Fugro FCV3000 ROV sending near real-time data to the operator on the vessel via a fibre optic multiplexor.

Data collection

The lidar laser data was processed using point cloud processing tools to compute the spatial relationships, measurements and orientations of the seabed structures.  The resulting deliverables included a 3D point cloud database, a dimensional report for each well, CAD files and a 360° animation of each well, modelled from the point cloud.

In addition to subsea lidar data, physical measurements were collected by the Fugro FCV3000 ROV using different sizes of V-gauges and rulers. Cross-referencing of the physical and lidar measurements with the original drawings helped identify discrepancies in existing drawing dimensions.

3D print process

To create a 1:1 model for the design of an appropriate ‘hot tap’ connector, a 3D print of the top of the well, with its damaged stub, at full scale was required. As the large size of the well cap structure made the cost prohibitive, a hybrid Computer Numeric Control (CNC) machining process, combined with a 3D print of the damaged part, was proposed as a viable alternative solution.

The first step was to re-process the point cloud data from the top of the well and then create 3D CAD models of the separate parts. However, this process proved more challenging than first thought due to the complexity of the shape. For this particular part the auto meshing algorithms which convert point clouds into surfaces did not perform well and as a result the CAD model was developed manually, which is also common when modelling complex shapes from terrestrial laser scans.

The part was then 3D printed by means of Fused Deposition Modelling (FDM) technology using Acrylonitrile Butadiene Styrene (ABS) thermoplastic material. One of the other two CNC machined parts was made from Acetal and the well cap from ultra-high-molecular-weight polyethylene (UHMWPE).

Fugro and 3D at Depth believe this is the first time accurate spatial data has been used to fabricate a subsea part using 3D printing, introducing the possibility of creating physical models for intervention planning and realising potential cost savings.

“While the individual sector scans provide millimetre accuracies, the wide area point cloud can provide a 3D dataset of centimetre accuracy across an entire drill centre,” confirms Adam Lowry, MD of 3D at Depth Pty Ltd. “Wide area point clouds, when used for planning, have proven to avoid costly surprises which are otherwise only discovered after the intervention vessel is actually on location.”

3D at Depth has been the recent recipient of the EEEGR Innovation award and are currently a finalist for the Subsea Energy Australia - Industry Innovation and Technology Award.

Did you know?

Approximately 44 million data points were collected at the well in 13.5 hours

 

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